What AI Means to a Retailer Dedicated to Customer Experience

Retailers are focused more than ever on quickly adjusting to changing customer preferences and demand. Specialty’s Café and Bakery is a great example of a retailer that is using data to drive decisions related to product development and selection, inventories, staffing, and more to attract and keep customers.

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Will AI Increase the Reach of BI and Analytics?

The business intelligence (BI) assembly line is broken, with adoption or utilization rates of only 30 percent in a typical organization, according to Gartner[1]. These adoption rates include all the users of the BI system – administrators who manage the system, analysts who build reports, and business users who consume reports for better decision making. This underutilization ignores employees outside the BI system who could be using valuable data to make better decisions. No one can argue that business performance and innovation are negatively impacted when data assets are not fully leveraged for decision making.

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Will your data product sparkle more if you build it or buy it?

“Should we build or buy?” is perhaps the diamond of enterprise IT: a question with at least 57 facets, each unique to a particular organization. In the past, your company may have made build-or-buy decisions when weighing options for enterprise software suites or departmental applications. Today, as more and more organizations look to data monetization to tap new revenue streams – IDC predicts that by 2020, in over half of Global 2000 firms, revenue growth from information-based products and services will be twice the growth rate of the balance of the product/service portfolio – the question emerges anew: should you build or buy your data product?

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Improve your company’s bottom line with analytics

The explosion of data in the financial services industry is creating new opportunities for business intelligence and analytics. At the same time, this explosion presents significant challenges. Over 2.7 zettabytes of data exist in the digital universe today. Every day, financial services companies seek to use these massive volumes of data to increase margins, reduce risk, boost customer satisfaction, and win in a globally competitive marketplace.

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